Bioactive small molecules produced by the human gut microbiome modulate <i>Vibrio cholerae</i> sessile and planktonic lifestyles
Bibliographic record
Abstract
Humans live in symbiosis with a diverse community of microorganisms, which has evolved to carry out many specific tasks that benefit the host, including protection against invading pathogens. Within the chemical diversity of the gastrointestinal tract, small molecules likely constitute chemical cues for the communication between the microbiota and pathogens. Therefore, we sought to investigate if molecules produced by the human gut microbiota show biological activity against the human pathogen Vibrio cholerae. To probe the effects of the gut metabolome on V. cholerae, we investigated its response to small-molecule extracts from human feces, from a complex bacterial community cultivated in vitro, and from culture supernatants of Enterocloster citroniae, Bacteroides thetaiotaomicron, and Bacteroides vulgatus. Using RNA sequencing, we determined the impact of the human gut metabolome on V. cholerae global gene expression. Among the genes downregulated in the presence of the fecal extract, the most overrepresented functional category was cell motility, which accounted for 39% of repressed genes. Repression of V. cholerae motility by the fecal extract was confirmed phenotypically, and E. citroniae extracts reproduced this phenotype. A complex in vitro microbial community led to increased motility, as did extracts from B. vulgatus, a species present in this community. Accordingly, mucin penetration was also repressed by fecal and E. citroniae extracts, suggesting that the phenotypes observed may have implications for host colonization. Together with previous studies, this work shows that small molecules from the gut metabolome may have a widespread, significant impact on microbe–microbe interactions established in the gut environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".